This project seeks to develop new statistical tools for evaluating gene-environment interactions and genetic susceptibility and to apply existing statistical tools in the analysis of gene-environment studies. Methodological work has proceeded in the area of improving study designs and associated techniques for data analysis. Geneticists have proposed using cases and their parents (case-parents triads) to study genetic effects on disease risk while overcoming the problem of population stratification or admixture. If a population consists of a number of distinct subpopulations that differ in baseline disease rates and in the frequency of a genetic variant, case-control studies may find associations between the variant and disease that arise simply because of the differing characteristics of the subpopulations. Such associations lack etiologic import. Case-parents triad designs can eliminate such potentially misleading associations. We are investigating designs that augment case-parents triads with control-parent triads to overcome some shortcomings of using case-parents triads alone. Such designs should more fully extend protection against population structure to studies of genotype and exposure together. We have also contributed to the analysis of data from several studies: of the interrelationship of aflatoxin exposure, hepatitis B virus infection, and p53 mutations within hepatocellular tumors; of the effects of polymorphisms in certain DNA repair genes on bladder cancer risk; and of how mutation frequency in various tetranucleotide repeat sequences depend on the bases involve in the repeat and on the particular carcinogenic exposure.